IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v17y2020i16p5675-d395170.html
   My bibliography  Save this article

A Comparative Study of Accident Risk Related to Speech-Based and Handheld Texting during a Sudden Braking Event in Urban Road Environments

Author

Listed:
  • Rui Fu

    (School of Automobile, Chang’an University, Xi’an 710064, China)

  • Yunxing Chen

    (School of Automobile, Chang’an University, Xi’an 710064, China
    School of Mechanical Engineering, Hubei University of Arts and Science, Xiangyang 441053, China)

  • Qingjin Xu

    (School of Automobile, Chang’an University, Xi’an 710064, China)

  • Yuxi Guo

    (School of Automobile, Chang’an University, Xi’an 710064, China)

  • Wei Yuan

    (School of Automobile, Chang’an University, Xi’an 710064, China)

Abstract

The use of mobile phones while driving is a very common phenomenon that has become one of the main causes of traffic accidents. Many studies on the effects of mobile phone use on accident risk have focused on conversation and texting; however, few studies have directly compared the impacts of speech-based texting and handheld texting on accident risk, especially during sudden braking events. This study aims to statistically model and quantify the effects of potential factors on accident risk associated with a sudden braking event in terms of the driving behavior characteristics of young drivers, the behavior of the lead vehicle (LV), and mobile phone distraction tasks (i.e., both speech-based and handheld texting). For this purpose, a total of fifty-five licensed young drivers completed a driving simulator experiment in a Chinese urban road environment under five driving conditions: baseline (no phone use), simple speech-based texting, complex speech-based texting, simple handheld texting, and complex handheld texting. Generalized linear mixed models were developed for the brake reaction time and rear-end accident probability during the sudden braking events. The results showed that handheld texting tasks led to a delayed response to the sudden braking events as compared to the baseline. However, speech-based texting tasks did not slow down the response. Moreover, drivers responded faster when the initial time headway was shorter, when the initial speed was higher, or when the LV deceleration rate was greater. The rear-end accident probability respectively increased by 2.41 and 2.77 times in the presence of simple and complex handheld texting while driving. Surprisingly, the effects of speech-based texting tasks were not significant, but the accident risk increased if drivers drove the vehicle with a shorter initial time headway or a higher LV deceleration rate. In summary, these findings suggest that the effects of mobile phone distraction tasks, driving behavior characteristics, and the behavior of the LV should be taken into consideration when developing algorithms for forward collision warning systems.

Suggested Citation

  • Rui Fu & Yunxing Chen & Qingjin Xu & Yuxi Guo & Wei Yuan, 2020. "A Comparative Study of Accident Risk Related to Speech-Based and Handheld Texting during a Sudden Braking Event in Urban Road Environments," IJERPH, MDPI, vol. 17(16), pages 1-18, August.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:16:p:5675-:d:395170
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/17/16/5675/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/17/16/5675/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Y. J. Zhang & F. Du & J. Wang & L. S. Ke & M. Wang & Y. Hu & M. Yu & G. H. Li & A. Y. Zhan, 2020. "A Safety Collision Avoidance Algorithm Based on Comprehensive Characteristics," Complexity, Hindawi, vol. 2020, pages 1-13, March.
    2. Yunxing Chen & Rui Fu & Qingjin Xu & Wei Yuan, 2020. "Mobile Phone Use in a Car-Following Situation: Impact on Time Headway and Effectiveness of Driver’s Rear-End Risk Compensation Behavior via a Driving Simulator Study," IJERPH, MDPI, vol. 17(4), pages 1-17, February.
    3. Oviedo-Trespalacios, Oscar, 2018. "Getting away with texting: Behavioural adaptation of drivers engaging in visual-manual tasks while driving," Transportation Research Part A: Policy and Practice, Elsevier, vol. 116(C), pages 112-121.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Gheorghe-Daniel Voinea & Cristian Cezar Postelnicu & Mihai Duguleana & Gheorghe-Leonte Mogan & Radu Socianu, 2020. "Driving Performance and Technology Acceptance Evaluation in Real Traffic of a Smartphone-Based Driver Assistance System," IJERPH, MDPI, vol. 17(19), pages 1-20, September.
    2. Gheorghe-Daniel Voinea & Răzvan Gabriel Boboc & Ioana-Diana Buzdugan & Csaba Antonya & George Yannis, 2023. "Texting While Driving: A Literature Review on Driving Simulator Studies," IJERPH, MDPI, vol. 20(5), pages 1-30, February.
    3. Răzvan Gabriel Boboc & Gheorghe Daniel Voinea & Ioana-Diana Buzdugan & Csaba Antonya, 2022. "Talking on the Phone While Driving: A Literature Review on Driving Simulator Studies," IJERPH, MDPI, vol. 19(17), pages 1-27, August.
    4. Mingyu Hou & Jianchuan Cheng & Feng Xiao & Chenzhu Wang, 2021. "Distracted Behavior of Pedestrians While Crossing Street: A Case Study in China," IJERPH, MDPI, vol. 18(1), pages 1-19, January.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Tyndall, Justin, 2021. "Pedestrian deaths and large vehicles," Economics of Transportation, Elsevier, vol. 26.
    2. Oviedo-Trespalacios, Oscar & Truelove, Verity & Watson, Barry & Hinton, Jane A., 2019. "The impact of road advertising signs on driver behaviour and implications for road safety: A critical systematic review," Transportation Research Part A: Policy and Practice, Elsevier, vol. 122(C), pages 85-98.
    3. Yuning Wang & Shuocheng Yang & Jinhao Li & Shaobing Xu & Jianqiang Wang, 2023. "An Emergency Driving Intervention System Designed for Driver Disability Scenarios Based on Emergency Risk Field," IJERPH, MDPI, vol. 20(3), pages 1-20, January.
    4. Helen Wells & Gemma Briggs & Leanne Savigar-Shaw, 2021. "The Inconvenient Truth About Mobile Phone Distraction: Understanding the Means, Motive and Opportunity for Driver Resistance to Legal and Safety Messages [‘Changes in Driver Behaviour as a Function," The British Journal of Criminology, Centre for Crime and Justice Studies, vol. 61(6), pages 1503-1520.
    5. Gheorghe-Daniel Voinea & Răzvan Gabriel Boboc & Ioana-Diana Buzdugan & Csaba Antonya & George Yannis, 2023. "Texting While Driving: A Literature Review on Driving Simulator Studies," IJERPH, MDPI, vol. 20(5), pages 1-30, February.
    6. Quy Nguyen-Phuoc, Duy & An Ngoc Nguyen, Nguyen & Nguyen, Minh Hieu & Ngoc Thi Nguyen, Ly & Oviedo-Trespalacios, Oscar, 2022. "Factors influencing road safety compliance among food delivery riders: An extension of the job demands-resources (JD-R) model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 166(C), pages 541-556.
    7. Yunxing Chen & Rui Fu & Qingjin Xu & Wei Yuan, 2020. "Mobile Phone Use in a Car-Following Situation: Impact on Time Headway and Effectiveness of Driver’s Rear-End Risk Compensation Behavior via a Driving Simulator Study," IJERPH, MDPI, vol. 17(4), pages 1-17, February.
    8. Răzvan Gabriel Boboc & Gheorghe Daniel Voinea & Ioana-Diana Buzdugan & Csaba Antonya, 2022. "Talking on the Phone While Driving: A Literature Review on Driving Simulator Studies," IJERPH, MDPI, vol. 19(17), pages 1-27, August.
    9. Haneen Abuzaid & Raghad Almashhour & Ghassan Abu-Lebdeh, 2024. "Driving towards Sustainability: A Neural Network-Based Prediction of the Traffic-Related Effects on Road Users in the UAE," Sustainability, MDPI, vol. 16(3), pages 1-22, January.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:17:y:2020:i:16:p:5675-:d:395170. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.